package com.atguigu.gmall.realtime.app.dwm;

import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONObject;
import com.atguigu.gmall.realtime.utils.MyKafkaUtil;
import org.apache.flink.api.common.functions.RichFilterFunction;
import org.apache.flink.api.common.state.StateTtlConfig;
import org.apache.flink.api.common.state.ValueState;
import org.apache.flink.api.common.state.ValueStateDescriptor;
import org.apache.flink.api.common.time.Time;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;

import java.text.SimpleDateFormat;

/**
 * Author: Felix
 * Date: 2022/1/19
 * Desc: 独立访客的计算
 * 需要启动的进程
 *      zk、kafka、logger.sh、BaseLogApp、UniqueVisitorApp
 * 执行流程
 *      运行模拟生成日志数据jar包
 *      将生成的日志发送给Nginx
 *      Nginx收到日志后将请求转发给日志采集服务器
 *      日志采集服务器处理日志
 *          打印、落盘、发送到kafka主题 ods_base_log
 *      BaseLogApp从ods_base_log主题中读取日志数据，进行分流
 *          启动日志--启动侧输出流--dwd_start_log
 *          曝光日志--曝光侧输出流--dwd_display_log
 *          页面日志--主流       --dwd_page_log
 *      UniqueVisitorApp从dwd_page_log中读取数据进行UV的过滤
 *
 */
public class UniqueVisitorApp {
    public static void main(String[] args) throws Exception {
        //TODO 1.基本环境准备
        //1.1 流处理环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //1.2 设置并行度
        env.setParallelism(4);

        //TODO 2.检查点相关设置(略)

        //TODO 3.从Kafka主题中读取数据
        //3.1 声明消费主题以及消费者组
        String topic = "dwd_page_log";
        String groupId = "unique_visitor_app_group";
        //3.2 创建消费者对象
        FlinkKafkaConsumer<String> kafkaSource = MyKafkaUtil.getKafkaSource(topic, groupId);
        //3.3 消费数据  封装为流
        DataStreamSource<String> kafkaDS = env.addSource(kafkaSource);
        //TODO 4.对流中数据类型进行转换    jsonStr->jsonObj
        SingleOutputStreamOperator<JSONObject> jsonObjDS = kafkaDS.map(JSON::parseObject);

        //TODO 5.按照mid对数据进行分组
        KeyedStream<JSONObject, String> keyedDS = jsonObjDS.keyBy(jsonObj -> jsonObj.getJSONObject("common").getString("mid"));

        //TODO 6.使用Flink的状态编程，完成独立访客的计算
        //用当某设备访问网站的时候，从状态中获取上次访问日期，如果上次访问日期不为空，并且是同一天，
        //说明今天以及访问过，直接将这条数据过滤掉；如果上次访问日期为空，或者不是同一天，说明今天还没有
        // 访问过，将当天访问日期放到状态中；
        //注意：我们这里是实时计算，统计当前的独立访客，所以我们设置状态的生命周期为1day
        SingleOutputStreamOperator<JSONObject> filterDS = keyedDS.filter(
            new RichFilterFunction<JSONObject>() {
                private SimpleDateFormat sdf;
                private ValueState<String> lastVisitDateState;

                @Override
                public void open(Configuration parameters) throws Exception {
                    sdf = new SimpleDateFormat("yyyyMMdd");
                    ValueStateDescriptor<String> valueStateDescriptor = new ValueStateDescriptor<>("lastVisitDateState", String.class);
                    StateTtlConfig stateTtlConfig = StateTtlConfig
                        .newBuilder(Time.days(1))
                        .setStateVisibility(StateTtlConfig.StateVisibility.NeverReturnExpired)
                        .setUpdateType(StateTtlConfig.UpdateType.OnCreateAndWrite)
                        .build();
                    valueStateDescriptor.enableTimeToLive(stateTtlConfig);
                    lastVisitDateState = getRuntimeContext().getState(valueStateDescriptor);
                }

                @Override
                public boolean filter(JSONObject jsonObj) throws Exception {
                    //获取上级页面id
                    String lastPageId = jsonObj.getJSONObject("page").getString("last_page_id");
                    if (lastPageId != null && lastPageId.length() > 0) {
                        return false;
                    }
                    //从状态中获取上次访问日期
                    String lastVisitDate = lastVisitDateState.value();
                    //获取当前访问日期
                    Long ts = jsonObj.getLong("ts");
                    String curVisitDate = sdf.format(ts);
                    if (lastVisitDate != null && lastVisitDate.length() > 0 && lastVisitDate.equals(curVisitDate)) {
                        return false;
                    } else {
                        lastVisitDateState.update(curVisitDate);
                        return true;
                    }
                }
            }
        );


        filterDS.print(">>>>>");

        //TODO 7.将独立访客数据写到kafka的dwm_unique_visitor主题中
        filterDS
            .map(jsonObj->jsonObj.toJSONString())
            .addSink(MyKafkaUtil.getKafkaSink("dwm_unique_visitor"));
        env.execute();
    }
}
